{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\".\\\\diyLogo.png\" alt=\"some_text\">\n",
    "<h1> 第二讲 程序设计基础</h1>\n",
    "<a id=backup></a>\n",
    "<H2>目录</H2>  \n",
    "\n",
    "[2.1 程序执行过程](#Section1)  \n",
    "[2.2 程序实例](#Section2)  \n",
    "[2.3 程序的基本结构](#Section3)     \n",
    "[2.4 顺序结构](#Section4)  \n",
    "[2.5 分支结构](#Section5)  \n",
    "[2.6 循环结构](#Section6) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id = Section1> </a>\n",
    "## 2.1 程序执行过程\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "a=!pip list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "numpy                     2.1.3\n",
      "matplotlib                3.9.2\n",
      "matplotlib-inline         0.1.7\n"
     ]
    }
   ],
   "source": [
    "for item in a:\n",
    "    if 'numpy' in item:\n",
    "        print(item)\n",
    "for item in a:\n",
    "    if 'matplotlib' in item:\n",
    "        print(item)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x24f73c28ed0>,\n",
       " <matplotlib.lines.Line2D at 0x24f75a28990>]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0,100*np.pi)\n",
    "a=1\n",
    "plt.plot(x,np.sin(8*x+np.pi/2),x,np.cos(x))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "请输入一个成绩"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "ename": "ExecutableNotFound",
     "evalue": "failed to execute WindowsPath('dot'), make sure the Graphviz executables are on your systems' PATH",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\backend\\execute.py:76\u001b[0m, in \u001b[0;36mrun_check\u001b[1;34m(cmd, input_lines, encoding, quiet, **kwargs)\u001b[0m\n\u001b[0;32m     75\u001b[0m         kwargs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mstdout\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m kwargs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mstderr\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m subprocess\u001b[38;5;241m.\u001b[39mPIPE\n\u001b[1;32m---> 76\u001b[0m     proc \u001b[38;5;241m=\u001b[39m \u001b[43m_run_input_lines\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcmd\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minput_lines\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     77\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\backend\\execute.py:96\u001b[0m, in \u001b[0;36m_run_input_lines\u001b[1;34m(cmd, input_lines, kwargs)\u001b[0m\n\u001b[0;32m     95\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_run_input_lines\u001b[39m(cmd, input_lines, \u001b[38;5;241m*\u001b[39m, kwargs):\n\u001b[1;32m---> 96\u001b[0m     popen \u001b[38;5;241m=\u001b[39m \u001b[43msubprocess\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mPopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcmd\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstdin\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msubprocess\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mPIPE\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     98\u001b[0m     stdin_write \u001b[38;5;241m=\u001b[39m popen\u001b[38;5;241m.\u001b[39mstdin\u001b[38;5;241m.\u001b[39mwrite\n",
      "File \u001b[1;32mC:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.11_3.11.2544.0_x64__qbz5n2kfra8p0\\Lib\\subprocess.py:1026\u001b[0m, in \u001b[0;36mPopen.__init__\u001b[1;34m(self, args, bufsize, executable, stdin, stdout, stderr, preexec_fn, close_fds, shell, cwd, env, universal_newlines, startupinfo, creationflags, restore_signals, start_new_session, pass_fds, user, group, extra_groups, encoding, errors, text, umask, pipesize, process_group)\u001b[0m\n\u001b[0;32m   1023\u001b[0m             \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstderr \u001b[38;5;241m=\u001b[39m io\u001b[38;5;241m.\u001b[39mTextIOWrapper(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstderr,\n\u001b[0;32m   1024\u001b[0m                     encoding\u001b[38;5;241m=\u001b[39mencoding, errors\u001b[38;5;241m=\u001b[39merrors)\n\u001b[1;32m-> 1026\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_execute_child\u001b[49m\u001b[43m(\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mexecutable\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpreexec_fn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mclose_fds\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1027\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mpass_fds\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcwd\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43menv\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1028\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mstartupinfo\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcreationflags\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mshell\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1029\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mp2cread\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mp2cwrite\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1030\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mc2pread\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mc2pwrite\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1031\u001b[0m \u001b[43m                        \u001b[49m\u001b[43merrread\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43merrwrite\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1032\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mrestore_signals\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1033\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mgid\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgids\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43muid\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mumask\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1034\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mstart_new_session\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprocess_group\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1035\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m:\n\u001b[0;32m   1036\u001b[0m     \u001b[38;5;66;03m# Cleanup if the child failed starting.\u001b[39;00m\n",
      "File \u001b[1;32mC:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.11_3.11.2544.0_x64__qbz5n2kfra8p0\\Lib\\subprocess.py:1538\u001b[0m, in \u001b[0;36mPopen._execute_child\u001b[1;34m(self, args, executable, preexec_fn, close_fds, pass_fds, cwd, env, startupinfo, creationflags, shell, p2cread, p2cwrite, c2pread, c2pwrite, errread, errwrite, unused_restore_signals, unused_gid, unused_gids, unused_uid, unused_umask, unused_start_new_session, unused_process_group)\u001b[0m\n\u001b[0;32m   1537\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m-> 1538\u001b[0m     hp, ht, pid, tid \u001b[38;5;241m=\u001b[39m \u001b[43m_winapi\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mCreateProcess\u001b[49m\u001b[43m(\u001b[49m\u001b[43mexecutable\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1539\u001b[0m \u001b[43m                             \u001b[49m\u001b[38;5;66;43;03m# no special security\u001b[39;49;00m\n\u001b[0;32m   1540\u001b[0m \u001b[43m                             \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[0;32m   1541\u001b[0m \u001b[43m                             \u001b[49m\u001b[38;5;28;43mint\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mclose_fds\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1542\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mcreationflags\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1543\u001b[0m \u001b[43m                             \u001b[49m\u001b[43menv\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1544\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mcwd\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1545\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mstartupinfo\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1546\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[0;32m   1547\u001b[0m     \u001b[38;5;66;03m# Child is launched. Close the parent's copy of those pipe\u001b[39;00m\n\u001b[0;32m   1548\u001b[0m     \u001b[38;5;66;03m# handles that only the child should have open.  You need\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   1551\u001b[0m     \u001b[38;5;66;03m# pipe will not close when the child process exits and the\u001b[39;00m\n\u001b[0;32m   1552\u001b[0m     \u001b[38;5;66;03m# ReadFile will hang.\u001b[39;00m\n",
      "\u001b[1;31mFileNotFoundError\u001b[0m: [WinError 2] 系统找不到指定的文件。",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[1;31mExecutableNotFound\u001b[0m                        Traceback (most recent call last)",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\IPython\\core\\formatters.py:977\u001b[0m, in \u001b[0;36mMimeBundleFormatter.__call__\u001b[1;34m(self, obj, include, exclude)\u001b[0m\n\u001b[0;32m    974\u001b[0m     method \u001b[38;5;241m=\u001b[39m get_real_method(obj, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprint_method)\n\u001b[0;32m    976\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m method \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m--> 977\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mmethod\u001b[49m\u001b[43m(\u001b[49m\u001b[43minclude\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minclude\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mexclude\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mexclude\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    978\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m    979\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\jupyter_integration.py:98\u001b[0m, in \u001b[0;36mJupyterIntegration._repr_mimebundle_\u001b[1;34m(self, include, exclude, **_)\u001b[0m\n\u001b[0;32m     96\u001b[0m include \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mset\u001b[39m(include) \u001b[38;5;28;01mif\u001b[39;00m include \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m {\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_jupyter_mimetype}\n\u001b[0;32m     97\u001b[0m include \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;28mset\u001b[39m(exclude \u001b[38;5;129;01mor\u001b[39;00m [])\n\u001b[1;32m---> 98\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m{\u001b[49m\u001b[43mmimetype\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mgetattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmethod_name\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     99\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mmimetype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmethod_name\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mMIME_TYPES\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mitems\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    100\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mmimetype\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43minclude\u001b[49m\u001b[43m}\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\jupyter_integration.py:98\u001b[0m, in \u001b[0;36m<dictcomp>\u001b[1;34m(.0)\u001b[0m\n\u001b[0;32m     96\u001b[0m include \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mset\u001b[39m(include) \u001b[38;5;28;01mif\u001b[39;00m include \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m {\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_jupyter_mimetype}\n\u001b[0;32m     97\u001b[0m include \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;28mset\u001b[39m(exclude \u001b[38;5;129;01mor\u001b[39;00m [])\n\u001b[1;32m---> 98\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m {mimetype: \u001b[38;5;28;43mgetattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmethod_name\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     99\u001b[0m         \u001b[38;5;28;01mfor\u001b[39;00m mimetype, method_name \u001b[38;5;129;01min\u001b[39;00m MIME_TYPES\u001b[38;5;241m.\u001b[39mitems()\n\u001b[0;32m    100\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m mimetype \u001b[38;5;129;01min\u001b[39;00m include}\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\jupyter_integration.py:112\u001b[0m, in \u001b[0;36mJupyterIntegration._repr_image_svg_xml\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    110\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_repr_image_svg_xml\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28mstr\u001b[39m:\n\u001b[0;32m    111\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Return the rendered graph as SVG string.\"\"\"\u001b[39;00m\n\u001b[1;32m--> 112\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpipe\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mformat\u001b[39;49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43msvg\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mSVG_ENCODING\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\piping.py:104\u001b[0m, in \u001b[0;36mPipe.pipe\u001b[1;34m(self, format, renderer, formatter, neato_no_op, quiet, engine, encoding)\u001b[0m\n\u001b[0;32m     55\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mpipe\u001b[39m(\u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m     56\u001b[0m          \u001b[38;5;28mformat\u001b[39m: typing\u001b[38;5;241m.\u001b[39mOptional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m     57\u001b[0m          renderer: typing\u001b[38;5;241m.\u001b[39mOptional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m     61\u001b[0m          engine: typing\u001b[38;5;241m.\u001b[39mOptional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m     62\u001b[0m          encoding: typing\u001b[38;5;241m.\u001b[39mOptional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m typing\u001b[38;5;241m.\u001b[39mUnion[\u001b[38;5;28mbytes\u001b[39m, \u001b[38;5;28mstr\u001b[39m]:\n\u001b[0;32m     63\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Return the source piped through the Graphviz layout command.\u001b[39;00m\n\u001b[0;32m     64\u001b[0m \n\u001b[0;32m     65\u001b[0m \u001b[38;5;124;03m    Args:\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    102\u001b[0m \u001b[38;5;124;03m        '<?xml version='\u001b[39;00m\n\u001b[0;32m    103\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m--> 104\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_pipe_legacy\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mformat\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m    105\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrenderer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    106\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mformatter\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mformatter\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    107\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mneato_no_op\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mneato_no_op\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    108\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mquiet\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mquiet\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    109\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mengine\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mengine\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    110\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\_tools.py:171\u001b[0m, in \u001b[0;36mdeprecate_positional_args.<locals>.decorator.<locals>.wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    162\u001b[0m     wanted \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mname\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mvalue\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m    163\u001b[0m                        \u001b[38;5;28;01mfor\u001b[39;00m name, value \u001b[38;5;129;01min\u001b[39;00m deprecated\u001b[38;5;241m.\u001b[39mitems())\n\u001b[0;32m    164\u001b[0m     warnings\u001b[38;5;241m.\u001b[39mwarn(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mThe signature of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfunc\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m will be reduced\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m    165\u001b[0m                   \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m to \u001b[39m\u001b[38;5;132;01m{\u001b[39;00msupported_number\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m positional args\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m    166\u001b[0m                   \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mlist\u001b[39m(supported)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m: pass \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mwanted\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m    167\u001b[0m                   \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m as keyword arg(s)\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m    168\u001b[0m                   stacklevel\u001b[38;5;241m=\u001b[39mstacklevel,\n\u001b[0;32m    169\u001b[0m                   category\u001b[38;5;241m=\u001b[39mcategory)\n\u001b[1;32m--> 171\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\piping.py:121\u001b[0m, in \u001b[0;36mPipe._pipe_legacy\u001b[1;34m(self, format, renderer, formatter, neato_no_op, quiet, engine, encoding)\u001b[0m\n\u001b[0;32m    112\u001b[0m \u001b[38;5;129m@_tools\u001b[39m\u001b[38;5;241m.\u001b[39mdeprecate_positional_args(supported_number\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m)\n\u001b[0;32m    113\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_pipe_legacy\u001b[39m(\u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m    114\u001b[0m                  \u001b[38;5;28mformat\u001b[39m: typing\u001b[38;5;241m.\u001b[39mOptional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    119\u001b[0m                  engine: typing\u001b[38;5;241m.\u001b[39mOptional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m    120\u001b[0m                  encoding: typing\u001b[38;5;241m.\u001b[39mOptional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m typing\u001b[38;5;241m.\u001b[39mUnion[\u001b[38;5;28mbytes\u001b[39m, \u001b[38;5;28mstr\u001b[39m]:\n\u001b[1;32m--> 121\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_pipe_future\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mformat\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m    122\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrenderer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    123\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mformatter\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mformatter\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    124\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mneato_no_op\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mneato_no_op\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    125\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mquiet\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mquiet\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    126\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mengine\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mengine\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    127\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\piping.py:149\u001b[0m, in \u001b[0;36mPipe._pipe_future\u001b[1;34m(self, format, renderer, formatter, neato_no_op, quiet, engine, encoding)\u001b[0m\n\u001b[0;32m    146\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m encoding \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m    147\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m codecs\u001b[38;5;241m.\u001b[39mlookup(encoding) \u001b[38;5;129;01mis\u001b[39;00m codecs\u001b[38;5;241m.\u001b[39mlookup(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mencoding):\n\u001b[0;32m    148\u001b[0m         \u001b[38;5;66;03m# common case: both stdin and stdout need the same encoding\u001b[39;00m\n\u001b[1;32m--> 149\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_pipe_lines_string\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    150\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m    151\u001b[0m         raw \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_pipe_lines(\u001b[38;5;241m*\u001b[39margs, input_encoding\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mencoding, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\backend\\piping.py:212\u001b[0m, in \u001b[0;36mpipe_lines_string\u001b[1;34m(engine, format, input_lines, encoding, renderer, formatter, neato_no_op, quiet)\u001b[0m\n\u001b[0;32m    206\u001b[0m cmd \u001b[38;5;241m=\u001b[39m dot_command\u001b[38;5;241m.\u001b[39mcommand(engine, \u001b[38;5;28mformat\u001b[39m,\n\u001b[0;32m    207\u001b[0m                           renderer\u001b[38;5;241m=\u001b[39mrenderer,\n\u001b[0;32m    208\u001b[0m                           formatter\u001b[38;5;241m=\u001b[39mformatter,\n\u001b[0;32m    209\u001b[0m                           neato_no_op\u001b[38;5;241m=\u001b[39mneato_no_op)\n\u001b[0;32m    210\u001b[0m kwargs \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m'\u001b[39m\u001b[38;5;124minput_lines\u001b[39m\u001b[38;5;124m'\u001b[39m: input_lines, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mencoding\u001b[39m\u001b[38;5;124m'\u001b[39m: encoding}\n\u001b[1;32m--> 212\u001b[0m proc \u001b[38;5;241m=\u001b[39m \u001b[43mexecute\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_check\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcmd\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcapture_output\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mquiet\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mquiet\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    213\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m proc\u001b[38;5;241m.\u001b[39mstdout\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\backend\\execute.py:81\u001b[0m, in \u001b[0;36mrun_check\u001b[1;34m(cmd, input_lines, encoding, quiet, **kwargs)\u001b[0m\n\u001b[0;32m     79\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m     80\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m e\u001b[38;5;241m.\u001b[39merrno \u001b[38;5;241m==\u001b[39m errno\u001b[38;5;241m.\u001b[39mENOENT:\n\u001b[1;32m---> 81\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m ExecutableNotFound(cmd) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01me\u001b[39;00m\n\u001b[0;32m     82\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m\n\u001b[0;32m     84\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m quiet \u001b[38;5;129;01mand\u001b[39;00m proc\u001b[38;5;241m.\u001b[39mstderr:\n",
      "\u001b[1;31mExecutableNotFound\u001b[0m: failed to execute WindowsPath('dot'), make sure the Graphviz executables are on your systems' PATH"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<graphviz.graphs.Digraph at 0x24f75c75610>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''import graphviz as viz\n",
    "viz.Digraph() '''\n",
    "from graphviz import Digraph\n",
    "dot = Digraph()\n",
    "dot.node('1','Start')\n",
    "dot.node('2','Input=>X')\n",
    "dot.node('3','for (i=0;i<0;i++)')\n",
    "dot.node('4','Plot Sinx and Cosx')\n",
    "dot.node('5','End')\n",
    "dot.edge('1','2')\n",
    "dot.edge('2','3')\n",
    "dot.edge('3','4',label='Yes')\n",
    "dot.edge('3','5',label='No')\n",
    "dot.edge('4','3')\n",
    "\n",
    "dot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "x = np.arange(-2 * np.pi, 2 * np.pi, 0.01)\n",
    "y = np.sin(x)\n",
    "plt.plot(x, y)\n",
    "plt.title('y = sin(x)')\n",
    "plt.xlabel('x')\n",
    "plt.ylabel('y')\n",
    "plt.grid(True)\n",
    "plt.show( )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        1         \n",
      "       1 1        \n",
      "      1 2 1       \n",
      "     1 3 3 1      \n",
      "    1 4 6 4 1     \n",
      "  1 5 10 10 5 1   \n",
      " 1 6 15 20 15 6 1 \n",
      "1 7 21 35 35 21 7 1\n",
      "1 8 28 56 70 56 28 8 1\n"
     ]
    }
   ],
   "source": [
    "def generate_pascals_triangle(num_rows):\n",
    "    if num_rows <= 0:\n",
    "        return []\n",
    "    \n",
    "    triangle = [[1]]\n",
    "    \n",
    "    for i in range(1, num_rows):\n",
    "        row = [1]\n",
    "        for j in range(1, i):\n",
    "            row.append(triangle[i-1][j-1] + triangle[i-1][j])\n",
    "        row.append(1)\n",
    "        triangle.append(row)\n",
    "    \n",
    "    return triangle\n",
    "\n",
    "def print_pascals_triangle(triangle):\n",
    "    for row in triangle:\n",
    "        print(' '.join(map(str, row)).center(len(triangle[-1])*2))\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    num_rows = int(input(\"请输入杨辉三角形的行数: \"))\n",
    "    triangle = generate_pascals_triangle(num_rows)\n",
    "    print_pascals_triangle(triangle)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         *\n",
      "        ***\n",
      "       *****\n",
      "      *******\n",
      "     *********\n",
      "    ***********\n",
      "   *************\n",
      "  ***************\n",
      " *****************\n",
      "*******************\n",
      "   |||\n",
      "   |||\n"
     ]
    }
   ],
   "source": [
    "def print_christmas_tree(height):\n",
    "    # 打印树冠部分\n",
    "    for i in range(height):\n",
    "        print(' ' * (height - i - 1) + '*' * (2 * i + 1))\n",
    "    \n",
    "    # 打印树干部分\n",
    "    trunk_width = height // 3 if height > 3 else 1\n",
    "    trunk_height = height // 4 if height > 4 else 1\n",
    "    trunk_space = (height - trunk_width) // 2\n",
    "    \n",
    "    for _ in range(trunk_height):\n",
    "        print(' ' * trunk_space + '|' * trunk_width)\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    tree_height = int(input(\"请输入圣诞树的高度: \"))\n",
    "    print_christmas_tree(tree_height)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "你的等级是: D\n"
     ]
    }
   ],
   "source": [
    "def determine_grade(score):\n",
    "     if score >= 90:\n",
    "         return 'A'\n",
    "     elif score >= 80:\n",
    "         return 'B'\n",
    "     elif score >= 70:\n",
    "         return 'C'\n",
    "     elif score >= 60:\n",
    "         return 'D'\n",
    "     else:\n",
    "         return 'F'\n",
    "\n",
    "def main():\n",
    "    try:\n",
    "         score = float(input(\"请输入成绩（0-100）: \"))\n",
    "         if not 0 <= score <= 100:\n",
    "             print(\"成绩必须在0到100之间。\")\n",
    "         else:\n",
    "            grade = determine_grade(score)\n",
    "            print(f\"你的等级是: {grade}\")\n",
    "    except ValueError:\n",
    "        print(\"请输入一个有效的数字。\")\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    main()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "ename": "ExecutableNotFound",
     "evalue": "failed to execute WindowsPath('dot'), make sure the Graphviz executables are on your systems' PATH",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\backend\\execute.py:76\u001b[0m, in \u001b[0;36mrun_check\u001b[1;34m(cmd, input_lines, encoding, quiet, **kwargs)\u001b[0m\n\u001b[0;32m     75\u001b[0m         kwargs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mstdout\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m kwargs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mstderr\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m subprocess\u001b[38;5;241m.\u001b[39mPIPE\n\u001b[1;32m---> 76\u001b[0m     proc \u001b[38;5;241m=\u001b[39m \u001b[43m_run_input_lines\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcmd\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minput_lines\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     77\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\backend\\execute.py:96\u001b[0m, in \u001b[0;36m_run_input_lines\u001b[1;34m(cmd, input_lines, kwargs)\u001b[0m\n\u001b[0;32m     95\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_run_input_lines\u001b[39m(cmd, input_lines, \u001b[38;5;241m*\u001b[39m, kwargs):\n\u001b[1;32m---> 96\u001b[0m     popen \u001b[38;5;241m=\u001b[39m \u001b[43msubprocess\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mPopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcmd\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstdin\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msubprocess\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mPIPE\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     98\u001b[0m     stdin_write \u001b[38;5;241m=\u001b[39m popen\u001b[38;5;241m.\u001b[39mstdin\u001b[38;5;241m.\u001b[39mwrite\n",
      "File \u001b[1;32mC:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.11_3.11.2544.0_x64__qbz5n2kfra8p0\\Lib\\subprocess.py:1026\u001b[0m, in \u001b[0;36mPopen.__init__\u001b[1;34m(self, args, bufsize, executable, stdin, stdout, stderr, preexec_fn, close_fds, shell, cwd, env, universal_newlines, startupinfo, creationflags, restore_signals, start_new_session, pass_fds, user, group, extra_groups, encoding, errors, text, umask, pipesize, process_group)\u001b[0m\n\u001b[0;32m   1023\u001b[0m             \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstderr \u001b[38;5;241m=\u001b[39m io\u001b[38;5;241m.\u001b[39mTextIOWrapper(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstderr,\n\u001b[0;32m   1024\u001b[0m                     encoding\u001b[38;5;241m=\u001b[39mencoding, errors\u001b[38;5;241m=\u001b[39merrors)\n\u001b[1;32m-> 1026\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_execute_child\u001b[49m\u001b[43m(\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mexecutable\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpreexec_fn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mclose_fds\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1027\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mpass_fds\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcwd\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43menv\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1028\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mstartupinfo\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcreationflags\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mshell\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1029\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mp2cread\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mp2cwrite\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1030\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mc2pread\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mc2pwrite\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1031\u001b[0m \u001b[43m                        \u001b[49m\u001b[43merrread\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43merrwrite\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1032\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mrestore_signals\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1033\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mgid\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgids\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43muid\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mumask\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1034\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mstart_new_session\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprocess_group\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1035\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m:\n\u001b[0;32m   1036\u001b[0m     \u001b[38;5;66;03m# Cleanup if the child failed starting.\u001b[39;00m\n",
      "File \u001b[1;32mC:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.11_3.11.2544.0_x64__qbz5n2kfra8p0\\Lib\\subprocess.py:1538\u001b[0m, in \u001b[0;36mPopen._execute_child\u001b[1;34m(self, args, executable, preexec_fn, close_fds, pass_fds, cwd, env, startupinfo, creationflags, shell, p2cread, p2cwrite, c2pread, c2pwrite, errread, errwrite, unused_restore_signals, unused_gid, unused_gids, unused_uid, unused_umask, unused_start_new_session, unused_process_group)\u001b[0m\n\u001b[0;32m   1537\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m-> 1538\u001b[0m     hp, ht, pid, tid \u001b[38;5;241m=\u001b[39m \u001b[43m_winapi\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mCreateProcess\u001b[49m\u001b[43m(\u001b[49m\u001b[43mexecutable\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1539\u001b[0m \u001b[43m                             \u001b[49m\u001b[38;5;66;43;03m# no special security\u001b[39;49;00m\n\u001b[0;32m   1540\u001b[0m \u001b[43m                             \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[0;32m   1541\u001b[0m \u001b[43m                             \u001b[49m\u001b[38;5;28;43mint\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mclose_fds\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1542\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mcreationflags\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1543\u001b[0m \u001b[43m                             \u001b[49m\u001b[43menv\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1544\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mcwd\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1545\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mstartupinfo\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1546\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[0;32m   1547\u001b[0m     \u001b[38;5;66;03m# Child is launched. Close the parent's copy of those pipe\u001b[39;00m\n\u001b[0;32m   1548\u001b[0m     \u001b[38;5;66;03m# handles that only the child should have open.  You need\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   1551\u001b[0m     \u001b[38;5;66;03m# pipe will not close when the child process exits and the\u001b[39;00m\n\u001b[0;32m   1552\u001b[0m     \u001b[38;5;66;03m# ReadFile will hang.\u001b[39;00m\n",
      "\u001b[1;31mFileNotFoundError\u001b[0m: [WinError 2] 系统找不到指定的文件。",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[1;31mExecutableNotFound\u001b[0m                        Traceback (most recent call last)",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\IPython\\core\\formatters.py:977\u001b[0m, in \u001b[0;36mMimeBundleFormatter.__call__\u001b[1;34m(self, obj, include, exclude)\u001b[0m\n\u001b[0;32m    974\u001b[0m     method \u001b[38;5;241m=\u001b[39m get_real_method(obj, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprint_method)\n\u001b[0;32m    976\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m method \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m--> 977\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mmethod\u001b[49m\u001b[43m(\u001b[49m\u001b[43minclude\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minclude\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mexclude\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mexclude\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    978\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m    979\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\jupyter_integration.py:98\u001b[0m, in \u001b[0;36mJupyterIntegration._repr_mimebundle_\u001b[1;34m(self, include, exclude, **_)\u001b[0m\n\u001b[0;32m     96\u001b[0m include \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mset\u001b[39m(include) \u001b[38;5;28;01mif\u001b[39;00m include \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m {\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_jupyter_mimetype}\n\u001b[0;32m     97\u001b[0m include \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;28mset\u001b[39m(exclude \u001b[38;5;129;01mor\u001b[39;00m [])\n\u001b[1;32m---> 98\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m{\u001b[49m\u001b[43mmimetype\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mgetattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmethod_name\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     99\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mmimetype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmethod_name\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mMIME_TYPES\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mitems\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    100\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mmimetype\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43minclude\u001b[49m\u001b[43m}\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\jupyter_integration.py:98\u001b[0m, in \u001b[0;36m<dictcomp>\u001b[1;34m(.0)\u001b[0m\n\u001b[0;32m     96\u001b[0m include \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mset\u001b[39m(include) \u001b[38;5;28;01mif\u001b[39;00m include \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m {\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_jupyter_mimetype}\n\u001b[0;32m     97\u001b[0m include \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;28mset\u001b[39m(exclude \u001b[38;5;129;01mor\u001b[39;00m [])\n\u001b[1;32m---> 98\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m {mimetype: \u001b[38;5;28;43mgetattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmethod_name\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     99\u001b[0m         \u001b[38;5;28;01mfor\u001b[39;00m mimetype, method_name \u001b[38;5;129;01min\u001b[39;00m MIME_TYPES\u001b[38;5;241m.\u001b[39mitems()\n\u001b[0;32m    100\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m mimetype \u001b[38;5;129;01min\u001b[39;00m include}\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\jupyter_integration.py:112\u001b[0m, in \u001b[0;36mJupyterIntegration._repr_image_svg_xml\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    110\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_repr_image_svg_xml\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28mstr\u001b[39m:\n\u001b[0;32m    111\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Return the rendered graph as SVG string.\"\"\"\u001b[39;00m\n\u001b[1;32m--> 112\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpipe\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mformat\u001b[39;49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43msvg\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mSVG_ENCODING\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\piping.py:104\u001b[0m, in \u001b[0;36mPipe.pipe\u001b[1;34m(self, format, renderer, formatter, neato_no_op, quiet, engine, encoding)\u001b[0m\n\u001b[0;32m     55\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mpipe\u001b[39m(\u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m     56\u001b[0m          \u001b[38;5;28mformat\u001b[39m: typing\u001b[38;5;241m.\u001b[39mOptional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m     57\u001b[0m          renderer: typing\u001b[38;5;241m.\u001b[39mOptional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m     61\u001b[0m          engine: typing\u001b[38;5;241m.\u001b[39mOptional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m     62\u001b[0m          encoding: typing\u001b[38;5;241m.\u001b[39mOptional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m typing\u001b[38;5;241m.\u001b[39mUnion[\u001b[38;5;28mbytes\u001b[39m, \u001b[38;5;28mstr\u001b[39m]:\n\u001b[0;32m     63\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Return the source piped through the Graphviz layout command.\u001b[39;00m\n\u001b[0;32m     64\u001b[0m \n\u001b[0;32m     65\u001b[0m \u001b[38;5;124;03m    Args:\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    102\u001b[0m \u001b[38;5;124;03m        '<?xml version='\u001b[39;00m\n\u001b[0;32m    103\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m--> 104\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_pipe_legacy\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mformat\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m    105\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrenderer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    106\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mformatter\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mformatter\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    107\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mneato_no_op\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mneato_no_op\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    108\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mquiet\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mquiet\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    109\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mengine\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mengine\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    110\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\_tools.py:171\u001b[0m, in \u001b[0;36mdeprecate_positional_args.<locals>.decorator.<locals>.wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    162\u001b[0m     wanted \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mname\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mvalue\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m    163\u001b[0m                        \u001b[38;5;28;01mfor\u001b[39;00m name, value \u001b[38;5;129;01min\u001b[39;00m deprecated\u001b[38;5;241m.\u001b[39mitems())\n\u001b[0;32m    164\u001b[0m     warnings\u001b[38;5;241m.\u001b[39mwarn(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mThe signature of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfunc\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m will be reduced\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m    165\u001b[0m                   \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m to \u001b[39m\u001b[38;5;132;01m{\u001b[39;00msupported_number\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m positional args\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m    166\u001b[0m                   \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mlist\u001b[39m(supported)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m: pass \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mwanted\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m    167\u001b[0m                   \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m as keyword arg(s)\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m    168\u001b[0m                   stacklevel\u001b[38;5;241m=\u001b[39mstacklevel,\n\u001b[0;32m    169\u001b[0m                   category\u001b[38;5;241m=\u001b[39mcategory)\n\u001b[1;32m--> 171\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\piping.py:121\u001b[0m, in \u001b[0;36mPipe._pipe_legacy\u001b[1;34m(self, format, renderer, formatter, neato_no_op, quiet, engine, encoding)\u001b[0m\n\u001b[0;32m    112\u001b[0m \u001b[38;5;129m@_tools\u001b[39m\u001b[38;5;241m.\u001b[39mdeprecate_positional_args(supported_number\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m)\n\u001b[0;32m    113\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_pipe_legacy\u001b[39m(\u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m    114\u001b[0m                  \u001b[38;5;28mformat\u001b[39m: typing\u001b[38;5;241m.\u001b[39mOptional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    119\u001b[0m                  engine: typing\u001b[38;5;241m.\u001b[39mOptional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m    120\u001b[0m                  encoding: typing\u001b[38;5;241m.\u001b[39mOptional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m typing\u001b[38;5;241m.\u001b[39mUnion[\u001b[38;5;28mbytes\u001b[39m, \u001b[38;5;28mstr\u001b[39m]:\n\u001b[1;32m--> 121\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_pipe_future\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mformat\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m    122\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrenderer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    123\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mformatter\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mformatter\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    124\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mneato_no_op\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mneato_no_op\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    125\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mquiet\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mquiet\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    126\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mengine\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mengine\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    127\u001b[0m \u001b[43m                             \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\piping.py:149\u001b[0m, in \u001b[0;36mPipe._pipe_future\u001b[1;34m(self, format, renderer, formatter, neato_no_op, quiet, engine, encoding)\u001b[0m\n\u001b[0;32m    146\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m encoding \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m    147\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m codecs\u001b[38;5;241m.\u001b[39mlookup(encoding) \u001b[38;5;129;01mis\u001b[39;00m codecs\u001b[38;5;241m.\u001b[39mlookup(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mencoding):\n\u001b[0;32m    148\u001b[0m         \u001b[38;5;66;03m# common case: both stdin and stdout need the same encoding\u001b[39;00m\n\u001b[1;32m--> 149\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_pipe_lines_string\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    150\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m    151\u001b[0m         raw \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_pipe_lines(\u001b[38;5;241m*\u001b[39margs, input_encoding\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mencoding, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\backend\\piping.py:212\u001b[0m, in \u001b[0;36mpipe_lines_string\u001b[1;34m(engine, format, input_lines, encoding, renderer, formatter, neato_no_op, quiet)\u001b[0m\n\u001b[0;32m    206\u001b[0m cmd \u001b[38;5;241m=\u001b[39m dot_command\u001b[38;5;241m.\u001b[39mcommand(engine, \u001b[38;5;28mformat\u001b[39m,\n\u001b[0;32m    207\u001b[0m                           renderer\u001b[38;5;241m=\u001b[39mrenderer,\n\u001b[0;32m    208\u001b[0m                           formatter\u001b[38;5;241m=\u001b[39mformatter,\n\u001b[0;32m    209\u001b[0m                           neato_no_op\u001b[38;5;241m=\u001b[39mneato_no_op)\n\u001b[0;32m    210\u001b[0m kwargs \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m'\u001b[39m\u001b[38;5;124minput_lines\u001b[39m\u001b[38;5;124m'\u001b[39m: input_lines, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mencoding\u001b[39m\u001b[38;5;124m'\u001b[39m: encoding}\n\u001b[1;32m--> 212\u001b[0m proc \u001b[38;5;241m=\u001b[39m \u001b[43mexecute\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_check\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcmd\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcapture_output\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mquiet\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mquiet\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    213\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m proc\u001b[38;5;241m.\u001b[39mstdout\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\graphviz\\backend\\execute.py:81\u001b[0m, in \u001b[0;36mrun_check\u001b[1;34m(cmd, input_lines, encoding, quiet, **kwargs)\u001b[0m\n\u001b[0;32m     79\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m     80\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m e\u001b[38;5;241m.\u001b[39merrno \u001b[38;5;241m==\u001b[39m errno\u001b[38;5;241m.\u001b[39mENOENT:\n\u001b[1;32m---> 81\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m ExecutableNotFound(cmd) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01me\u001b[39;00m\n\u001b[0;32m     82\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m\n\u001b[0;32m     84\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m quiet \u001b[38;5;129;01mand\u001b[39;00m proc\u001b[38;5;241m.\u001b[39mstderr:\n",
      "\u001b[1;31mExecutableNotFound\u001b[0m: failed to execute WindowsPath('dot'), make sure the Graphviz executables are on your systems' PATH"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<graphviz.graphs.Digraph at 0x179bb274110>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import graphviz\n",
    "dot=graphviz.Digraph(comment='the round table',name=\"分支结构\",node_attr={'shape':'box'})\n",
    "dot.node('1','开始')\n",
    "dot.node('2','请输入成绩=?', shape='parallelogram')\n",
    "dot.node('3','x是否大等于90?', shape='diamond')\n",
    "dot.node('4','x是否大等于80?', shape='diamond')\n",
    "dot.node('5','x是否大等于70?', shape='diamond')\n",
    "dot.node('6','x是否大等于60?', shape='diamond')\n",
    "dot.node('a','Print A')\n",
    "dot.node('b','Print B')\n",
    "dot.node('c','Print C')\n",
    "dot.node('d','Print D')\n",
    "dot.node('e','Print E')\n",
    "dot.node('7','结束')\n",
    "dot.edges(['12','23','a7','b7','c7','d7','e7'])\n",
    "dot.edge('3','a',label='Yes')\n",
    "dot.edge('3','4',label='No')\n",
    "dot.edge('4','b',label='Yes')\n",
    "dot.edge('4','5',label='No')\n",
    "dot.edge('5','c',label='Yes')\n",
    "dot.edge('5','6',label='No')\n",
    "dot.edge('6','d',label='Yes')\n",
    "dot.edge('6','e',label='No')\n",
    "dot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "show_heigth = 25\n",
    "show_width = 100\n",
    "#这两个数字是调出来的\n",
    "\n",
    "ascii_char = list(\n",
    "    \"$@B%8&WM#*oahkbdpqwmZO0QLCJUYXzcvunxrjft/\\|()1{}[]?-_+~<>i!lI;:,\\\"^`'. \")\n",
    "#生成一个ascii字符列表\n",
    "char_len = len(ascii_char)\n",
    "\n",
    "pic = plt.imread(\".\\\\R-C.jpeg\")\n",
    "#使用plt.imread方法来读取图像，对于彩图，返回size = heigth*width*3的图像\n",
    "#matplotlib 中色彩排列是R G B\n",
    "#opencv的cv2中色彩排列是B G R\n",
    "\n",
    "pic_heigth, pic_width, _ = pic.shape\n",
    "#获取图像的高、宽\n",
    "\n",
    "gray = 0.2126 * pic[:, :, 0] + 0.7152 * pic[:, :, 1] + 0.0722 * pic[:, :, 2]\n",
    "#RGB转灰度图的公式 gray = 0.2126 * r + 0.7152 * g + 0.0722 * b\n",
    "\n",
    "#思路就是根据灰度值，映射到相应的ascii_char\n",
    "for i in range(show_heigth):\n",
    "    #根据比例映射到对应的像素\n",
    "    y = int(i * pic_heigth / show_heigth)\n",
    "    text = \"\"\n",
    "    for j in range(show_width):\n",
    "        x = int(j * pic_width / show_width)\n",
    "        text += ascii_char[int(gray[y][x] / 256 * char_len)]\n",
    "    print(text)"
   ]
  }
 ],
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.9"
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